Machine learning (ML) is getting a lot of attention at the moment.
This is partly because a slew of new companies are emerging which are
using it in innovative ways. And partly because it can get easily
subsumed into the fuss and furore about AI and the rise of evil robot
intelligence. Graph technology, on the other hand, is something which
takes more of a back seat and yet, in a lot of ways, also sits at the
forefront of the big data and analytics movement. “We firmly believe is that it's at the intersection of machine
learning and graph technology where the next evolution lies and where
new disruptive companies are emerging,” says Ash Damle, Founder and CEO
at Lumiata which helps healthcare organisations makes predictions.“It's only recently that companies can use graph at true scale and,
now, by integrating with ML, we're moving much more into a core
understanding of artificial intelligence, deep neural networks and image
recognition.”So, in the simplest terms what are these two technologies?At the most basic level machine learning takes large quantities of
data to make predictions about future events. While graph technology is
more concerned with the relationship between different data points.Claus Jepsen, Chief Architect, R&D at Unit4 which provides enterprise applications, summarises:“Machine Learning is really the umbrella and graph technology is a way of representing data when using machine learning.”While Peter Duffy, CTO of capacity planning as a service provider, Sumerian adds, this means: “There is huge potential for businesses to take advantage of both.”David Thompson, Sr. Director of Product Management atLightCyber
further clarifies: “Graph technology can be considered a type or
technique of machine learning, or, at a minimum, aspects of graph
technology have strong application to machine learning.”Read more...

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Hello, my name is Helge Scherlund and I am the Education Editor and Online Educator of this personal weblog and the founder of eLearning • Computer-Mediated Communication Center.
I have an education in the teaching adults and adult learning from Roskilde University, with Computer-Mediated Communication (CMC) and Human Resource Development (HRD) as specially studied subjects. I am the author of several articles and publications about the use of decision support tools, e-learning and computer-mediated communication. I am a member of The Danish Mathematical Society (DMF), The Danish Society for Theoretical Statistics (DSTS) and an individual member of the European Mathematical Society (EMS). Note: Comments published here are purely my own and do not reflect those of my current or future employers or other organizations.